SizeOverviewCombinedPlots

library(tidyverse)
library(here)
library(plotly)
library(htmlwidgets)
library(patchwork)
library(gridExtra)

load(file = here("data/data_tidy.RData")) # load object data_tidy

BodyLengths <- tibble(Species = c("Ceriodaphnia sp.", "C. megalops", "D. cucullata", "D. curvirostris", "D. hyalina var. gellata", "D. hyalina var. lacustris", "D. hyalina", "D. longispina", "D. pulex", "D. magna", "Calanoid copepods", "Cyclops", "Bosmina coregoni", "B. longirostris", "Sida sp.", "S. crystallina", "Chydorus ovalis", "Eurycercus lamellatus", "Alona spp.", "A. quadrangularis", "Asplanchna", "Keratella spp.", "Ostracod", "Diaptomus"),
                      BodyLength = c(0.4636, 0.925, 0.8593, 1.58, 0.9064, 0.9064, 0.9064, 1.0347, 1.1656, 1.4214, 0.6860, 1.0369, 0.4230, 0.3637, 0.5075, 0.5075, 0.475, 1.975, 0.5235, 0.9679, 0.4747, 0.3495, 1.25, 0.9886)) # species and their body sizes

data <- left_join(data_tidy, BodyLengths, by = "Species") # add species body size to the dataframe

data <- mutate(data, SizeClass = case_when(BodyLength <= 0.6 ~ "Small (<= 0.6 mm)",
                                           BodyLength <= 1.0 ~ "Medium ( 0.6 < x <= 1.0 mm)",
                                           BodyLength > 1.0 ~ "Large (> 1.0 mm)"))
plotlist <- list()
lakes <- unique(data$LakeName)
years <- unique(data$Year)

for (i in 1:length(lakes)){
  Ldata <- filter(data, LakeName == lakes[i])
  
  for (j in 1:length(years)){
    Ydata <- filter(Ldata, Year == years[j])
    
    if (nrow(Ydata) > 0) {
      
      summary <- Ydata %>% group_by(Species, SizeClass, Date) %>% summarize(sum_counts = sum(Counts, na.rm = TRUE),
                                                                            sum_total = sum(Total_individuals, na.rm = TRUE)) # Calculate counts per Date
      
      summary <- summary %>% group_by(SizeClass, Date, sum_total) %>% summarize(sum_counts = sum(sum_counts, na.rm = TRUE))
      
      summaryV <- Ydata %>% group_by(Species, Date) %>% summarize(sum_counts = sum(Counts, na.rm = TRUE),
                                                                  sum_total = sum(Total_individuals, na.rm = TRUE))
      
      summaryV <- summaryV %>% mutate("Relative_abundance" = sum_counts / sum_total * 100) # Calculate relative abundance per Date
      
      summaryW <- left_join(summaryV, BodyLengths, by = "Species")
      
      WeightedMean <- summaryW %>% group_by(Date) %>% summarize(WeightedMean_mm = weighted.mean(BodyLength, Relative_abundance))
      
      summary <- summary %>% mutate("Relative_abundance" = sum_counts / sum_total * 100) # Calculate relative abundance per Date
      
      result <- summary %>% ggplot(aes(x = Date, y = Relative_abundance, fill = SizeClass))+
        geom_col(color = "Black", linewidth = 0.05)+
        labs(x = "Month", y = "Relative abundance (%)", title = paste0(lakes[[i]], " in ", years[[j]]))+
        theme_minimal()
      
      tbl <- tableGrob(WeightedMean)
      
      print(wrap_plots(result, tbl))
      
    } else {
      warning(paste0("No data for ", lakes[[i]], " in the year ", years[[j]]))
    }
  }
}

## Warning: No data for Coneries Lake in the year 2010

## Warning: No data for Coneries Lake in the year 2011

## Warning: No data for Coneries Lake in the year 2012

## Warning: Removed 3 rows containing missing values (`position_stack()`).

## Warning: No data for Main Pond in the year 2010

## Warning: No data for Main Pond in the year 2011

## Warning: No data for Main Pond in the year 2012

## Warning: Removed 3 rows containing missing values (`position_stack()`).

## Warning: No data for Church Pond in the year 2010

## Warning: No data for Church Pond in the year 2011

## Warning: No data for Church Pond in the year 2012

## Warning: No data for Beeston Pond in the year 2010

## Warning: No data for Beeston Pond in the year 2011

## Warning: No data for Beeston Pond in the year 2012